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Forecast Model of Comprehensive Transport Freight Index Considering Macro Economy in China

  • Yanli Ma*
  • , Jieyu Zhu
  • , Yining Lou
  • *Corresponding author for this work
  • School of Transportation Science and Engineering, Harbin Institute of Technology
  • University College London

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

To better construct the coordinated development of the comprehensive transportation system, the prediction model of comprehensive freight index in China was studied. Basic indicators of production and supply, benefits and macroeconomic were selected. Cluster analysis was used to divide the indicators into 13 leading indicators and 13 synchronous indicators. Factor analysis was used to analyze the importance of each leading indicator. The characteristic quantities of freight index were determined and the Granger causality test was conducted between the four indexes and the five characteristic quantities respectively. The relationship model between each freight index and characteristic quantity was constructed, and the validity of the model was verified. Results show that the freight indexes are volatile. There is a stable relationship between characteristic quantity and freight index. The error of forecast and actual value of is within 10%, verifying the validity of the model. The results can provide theoretical support for forecasting the development trends of freight transport among various transport modes. The comprehensive transport will be improved to provide a decision-making basis for the national macro-department to make policies.

Original languageEnglish
Title of host publicationGreen Connected Automated Transportation and Safety - Proceedings of the 11th International Conference on Green Intelligent Transportation Systems and Safety
EditorsWuhong Wang, Yanyan Chen, Zhengbing He, Xiaobei Jiang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages231-244
Number of pages14
ISBN (Print)9789811654282
DOIs
StatePublished - 2022
Externally publishedYes
Event11th International Conference on Green Intelligent Transportation Systems and Safety, 2020 - Beijing, China
Duration: 17 Oct 202019 Oct 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume775
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference11th International Conference on Green Intelligent Transportation Systems and Safety, 2020
Country/TerritoryChina
CityBeijing
Period17/10/2019/10/20

Keywords

  • Clustering analysis
  • Comprehensive transportation
  • Forecast model
  • Freight index
  • Granger causality test

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